By analyzing associations between community-level factors and inflammation-related proteins, this study provides new molecular insights into how social context may relate to biological risk, identifies proteomic patterns that could inform the development of community-level interventions, and underscores the utility of integrating multi-omics approaches to investigate biological pathways relevant to health disparities research.
Abstract
Background
Inflammation is a key driver of age-related disease and has been associated with social conditions. We examined how cumulative community-level social and structural disadvantage is associated with inflammatory proteomic profiles in older Black adults.
Methods
We employed data from the Minority Aging Research Study and the Rush Clinical Core, including the Social Vulnerability Index (SVI; global score and four domains) and 92 plasma inflammatory proteins (Olink® Target-96 Inflammation). Cross-sectional associations between each SVI metric and inflammatory proteins (principal component (PC)-derived global proteomic profile and protein-specific) were assessed using multivariable linear models (demographic, behavioral, and individual-level socioeconomic factors adjusted), with additional sex-by-SVI interaction terms. In a secondary analysis, we replaced SVI with the Index of Concentration at the Extremes (ICE) for household income (ICEincome).
Results
A total of 580 participants (mean (SD) age of 74.9 (6.50) years; 79.7% women) had global SVI and proteomics assessed. Lower household composition (SVIHHC) was associated with the primary global proteomic profile, represented by the 1st proteomic PC (beta = -0.429, p-value = 0.019). A secondary exploratory analysis using the first five proteomic PCs showed that higher minority status/language (SVIMSL) and socioeconomic status (SVISES) were associated with an inflammatory proteomic profile (SVIMSL-PC3: beta=0.160, p-value = 0.048; SVISES-PC2: beta = 0.286, p-value = 0.012). In protein-specific analyses, no SVI-protein associations were found. We found an SVIHHC-by-sex interaction for interleukin-10 receptor alpha (IL-10RA; beta = -0.258, p-value = 5.01×10-4), and among men, SVIMSL was associated with Sirtuin 2 (beta = -0.397, p-value = 8.51×10-04) and STAM binding protein (beta = -0.304, p-value = 9.87×10-04). ICEincome was inversely associated with the global proteomic profile (beta = -0.233, p-value = 0.051), and an ICEincome-by-sex interaction was found for IL-10RA (beta=0.279, p-value = 4.66×10-04).
Conclusions
By analyzing associations between community-level factors and inflammation-related proteins, our study provides new molecular insights into how social context may relate to biological risk, identifies proteomic patterns that could inform the development of community-level interventions, and underscores the utility of integrating multi-omics approaches to investigate biological pathways relevant to health disparities research.
It is found that socioeconomic adversity influences not only inflammatory pathways but also distinct biological aging processes, including metabolomic aging, and that socioeconomic adversity influences not only inflammatory pathways but also distinct biological aging processes.
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